There’s no doubt about it — artificial intelligence is here, and it’s poised to make a tremendous impact on virtually every industry. While many companies already recognize AI as a competitive advantage, this perception will only increase as the technology matures and organizations gain an even deeper understanding of its capabilities and full potential.
To help you prepare for these impending changes, I’ve picked out four AI trends that I believe will affect organizations and consumers next year.
1. People start discerning between fake AI and real AI
Before cloud was mainstream, many companies sold installed software applications or bought hardware and claimed that they were the cloud. In reality, all they were doing was packaging their products in different ways. AI is going through a similar sort of ultra-hype cycle. As the number of real AI products grows, so does the prevalence of fake AI.
These days, it seems like there’s a constant stream of new companies touting their “AI-powered” platform. But while adding AI to your business plan might attract more investors, it won’t do much else if it can’t deliver insights and automated action to your customers.
Unfortunately, some companies fall prey to fake AI or waste money on first-generation science experiments that don’t provide any real value. Once this happens, they’ll need to reset their expectations on what AI can do. The good news is that as more and more buyers, consumers, and businesses invest in and start driving real results from AI, the real AI products will rise to the top, and it will become easier to discern between the fake and real AI products. In general, managers and executives will go back to the basics and start focusing on value and data rather than data science.
2. We redefine data science skill sets
The Harvard Business Review crowned data scientist the sexiest job of the 21st century back in 2012 when technology companies realized they were sitting on treasure troves of data. Today, there is a huge shortage of data science talent, and according to IBM, the demand for data scientists will soar 28 percent by 2020. As a result, companies across industries are clamoring to invest in and build their own data science teams. To meet demand, we’re seeing a fundamental shift in how data scientists are trained and hired. Rather than recruiting data scientists straight out of academia, companies and startups across industries are investing in professionals at the top of their fields and are fronting the bill to teach them data science skills.
Over the next year, as the data science talent pool grows from the inside out, we’ll begin to see data science permeate into even more industries. We can also expect to see different academic programs offering a data science track, from architecture to medicine and engineering. Eventually, we’ll see a decline in the number of “pure” data scientists and an increase in professionals who have data science skills that are relevant to their respective fields. Data science will follow the same route as statistics or programming, which are more or less taught across all disciplines. This shift will give rise to a set of domain- and vertical-specific AI product managers — whom we’ve had a lack of until now — who know enough about data and data science and can translate business problems to AI-driven solutions.
3. Spam as you know it could die (really!)
Marketers have talked about one-to-one marketing and personalization at scale for years, but 2018 could be the year this dream actually becomes a reality. As AI technology gets more sophisticated and capable of ingesting and analyzing public data sources like blogs and SEC filings, marketers will get a clear window into what their prospects and customers are searching for, researching, and writing about.
They can take these massive amounts of public data and aggregate it at a business level, with enough context to truly understand our buyers and start individually relevant conversations automatically. As this becomes a more common practice, spam as we know it could die its final death.
This is an exciting prediction for marketers, who’ve struggled to connect with their customers, but it’s equally exciting for consumers, who in the past few years have been more exposed to AI and personalization. With the rise of technologies like Amazon Alexa and Siri on Apple Watch, AI is more normalized for customers. Five years ago, customers thought it was invasive when companies knew specific details about their past order history or recommended items based on recent internet searches or Facebook likes. Today, receiving personalized product recommendations or communications has become expected and desired.
4. AI moves beyond startups to the enterprise
While a majority of the hype around AI is clustered in the startup and VC world, we’re starting to see larger companies across industries pay attention to the technology. Companies as diverse as Walgreens and Autocad fund and develop their own AI-based products. This will continue to take shape next year as more enterprise companies toss their hats into the ring. And chances are, AI will be more successful in those companies since they have more proprietary data and access to business workflows. They’re at an advantage when it comes to driving innovation because, as we all know, data is the key to smarter, more effective AI technology.
It’s an exciting time for AI. The technology and our understanding of what it’s good for have advanced over the past few years, and AI is becoming even more “real” and applicable every day. In 2018, we’ll see consumers and companies raise the bar for future advancements, and I expect AI will rise to the occasion.
Aman Naimat is senior vice president of technology at Demandbase, an artificial intelligence platform for the next generation of B2B marketing.